The aim of this study was to explore the relationship between the amygdala and human sex drive. We compared amygdalar volume in groups of patients with or without sexual changes after temporal lobe resection and in age-matched neurologically normal subjects. Forty-five patients with intractable temporal lobe epilepsy who underwent surgical resection in the Comprehensive Epilepsy Program at the Austin and Repatriation Medical Centre completed a semistructured interview and questionnaire relating to sexual outcome after surgery. Volumetric analyses of both amygdalae were conducted on the patients' preoperative T(1)-weighted magnetic resonance imaging scans and those of 46 neurologically normal controls. Patients who reported a postoperative sexual increase had a significantly larger amygdalar volume contralateral to the site of their resective surgery than patients with a sexual decrease or no change than control subjects. There was a significant positive relationship between contralateral amygdalar volume and the maximum degree of sexual change. We have demonstrated a relationship between contralateral amygdalar volume and sexual outcome in patients undergoing temporal lobe resection. This finding provides evidence for an important role of the amygdala in regulating human sexual behavior. A larger contralateral amygdala may contribute to the expression of increased or improved sexuality after temporal lobe resection.
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http://dx.doi.org/10.1002/ana.10997 | DOI Listing |
Appl Neuropsychol Adult
December 2024
Department of Clinical Psychology, William James College, Newton, MA, USA.
Objective: Little is known about the relative contribution of frontal and anterior temporal lobes in semantic knowledge of social norms in frontotemporal dementia (FTD). Therefore, this study examined performance of FTD patients with either frontal (F-FTD, left temporal (LT-FTD) or bitemporal lobe atrophy (BT-FTD) on the Social Norms Questionnaire (SNQ) and explored what accounts for the variance in the SNQ-break norm subscale (i.e.
View Article and Find Full Text PDFJ Integr Neurosci
December 2024
Department of Radiology, Affiliated Hospital of North Sichuan Medical College, 637000 Nanchong, Sichuan, China.
Background: The relationship between subregion atrophy in the entire temporal lobe and subcortical nuclei and cognitive decline at various stages of Alzheimer's disease (AD) is unclear.
Methods: We selected 711 participants from the AD Neuroimaging Initiative (ADNI) database, which included 195 cases of cognitively normal (CN), 271 cases of early Mild cognitive impairment (MCI) (EMCI), 132 cases of late MCI (LMCI), and 113 cases of AD. we looked at how subregion atrophy in the temporal lobe and subcortical nuclei correlated with cognition at different stages of AD.
J Inflamm Res
December 2024
Department of Neurology, Yancheng Third People's Hospital, Yancheng, People's Republic of China.
Objective: The aims of this study were to investigate clinical factors associated with encephalitis relapse and chronic epilepsy development, and to evaluate the effectiveness of immunotherapy on encephalitis relapse.
Methods: Patients with autoimmune encephalitis diagnosed as positive for neuronal surface antibodies in five general hospitals were included. A minimum 12-month follow-up period was conducted, and binary logistic regression analysis was used to identify predictors of encephalitis relapse and chronic epilepsy development.
Netw Neurosci
December 2024
Department of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand.
Connectomes' topological organization can be quantified using graph theory. Here, we investigated brain networks in higher dimensional spaces defined by up to 10 graph theoretic nodal properties. These properties assign a score to nodes, reflecting their meaning in the network.
View Article and Find Full Text PDFNetw Neurosci
December 2024
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
Understanding the differences between functional and structural human brain connectivity has been a focus of an extensive amount of neuroscience research. We employ a novel approach using the multinomial stochastic block model (MSBM) to explicitly extract components that characterize prominent differences across graphs. We analyze structural and functional connectomes derived from high-resolution diffusion-weighted MRI and fMRI scans of 250 Human Connectome Project subjects, analyzed at group connectivity level across 50 subjects.
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